659 Courses

Duration 3 Days 18 CPD hours This course is intended for Experienced system administrators and network administrators Customers, cloud architects, systems engineers, data center administrators Network administrators with experience in managed services or managing a Telco Cloud environment Overview By the end of the course, you should be able to meet the following objectives: Deploy VMware Telco Cloud Service Assurance Manage VMware Telco Cloud Service Assurance to satisfy Telco cloud provider needs Discuss configurable options for VMware Telco Cloud Service Assurance Identify and configure different data sources which are used with VMware Telco Cloud Service Assurance Configure different collectors in VMware Telco Cloud Service Assurance Identify the Root Cause Analysis options with VMware Telco Cloud Service Assurance Discuss data collection in VMware Telco Cloud Service Assurance Explain root cause analysis in VMware Telco Cloud Service Assurance Navigate through the logs for troubleshooting This three-day, hands-on training course provides the knowledge, skills, and tools to achieve competency in installing, configuring, and managing the VMware Telco Cloud Service Assurance environment. In this course, you are introduced to the installation methods of VMware Telco Cloud Service Assurance? across various supported platforms and troubleshooting tools that help you install, manage, and troubleshoot your VMware Telco Cloud Service Assurance environment. In addition, you are presented with various types of configuration options, which you will identify, analyze, and navigate through as you explore the UI and configurable options of the product. Course Introduction Introduction and course logistics Course objectives Introduction to VMware Telco Cloud Service Assurance Describe the features of VMware Telco Cloud Service Assurance List the capabilities of VMware Telco Cloud Service Assurance Discuss the use cases of VMware Telco Cloud Service Assurance Describe the role played by VMware Telco Cloud Service Assurance components in delivering service assurance Deploying VMware Telco Cloud Service Assurance Explain different deployment options of VMware Telco Cloud Service Assurance Identify different deployment methods of VMware Telco Cloud Service Assurance Discuss different phases in deploying VMware Telco Cloud Service Assurance Identify different footprints available for HA based and non-HA based installation of VMware Telco Cloud Service Assurance Describe the SMARTs components of VMware Telco Cloud Service Assurance Deploy VMware Telco Cloud Service Assurance User Access Control Describe the features Role-based Access Control (RBAC) Outline the role of Keycloak in implementing RBAC in VMware Telco Cloud Service Assurance Configure user federation in Keycloak Use the VMware Telco Cloud Service Assurance UI to manage RBAC Create policies in VMware Telco Cloud Service Assurance that align with job roles Services and User Interface Configurations Describe the architecture of logical switching Describe the core services on a TCSA cluster Discuss the Global Manager or Service Assurance Manager (SAM), IP Domain Manager, Server Manager (ESM) Discuss VMware Telco Cloud Service Assurance UI Overview Explain Working with Notifications Elaborate Configuring Summary's Describe Accessing Notification Details Explain Viewing and configuring Topologies List Customizing Topologies Describe Topology Explorer Explain Collecting Troubleshooting Information Discuss Custom models Describe how compute resources are provided to VMware Telco Cloud Service Assurance Describe how storage is provided to VMware Telco Cloud Service Assurance Configure and manage VMware Telco Cloud Service Assurance Discuss configurable options for VMware Telco Cloud Service Assurance Day 1 and Day 2 Operations Review the architecture of logical routing and NSX Edge nodes Identify different data sources to be used with VMware Telco Cloud Service Assurance Configure different collectors with VMware Telco Cloud Service Assurance Describe Alarms and Thresholds Demonstrate how to configure alarms with VMware Telco Cloud Service Assurance Explain how to setup thresholds and timelines in VMware Telco Cloud Service Assurance Define Catalog management and sharing catalogs inside and between organizations. Identify the steps to import or upload data into catalogs. Explain the purpose of catalogs and How to Create a catalog organization. Describe the Purpose and Usage of Open Virtualization Format (OVA) and Custom vApp or VM Properties. Discuss vApp Templates Logs and Troubleshooting Review the architecture of the Distributed Firewall Discuss VMware Telco Cloud Service Assurance installations logs List Smarts installation logs Explain backup and restore options of VMware Telco Cloud Service Assurance Identify the approach for troubleshooting containerized services Discuss monitoring services

Duration 1 Days 6 CPD hours This course is intended for This course is intended for anybody interested in learning what is Azure Services, considering a job or career in Azure Services, or considering obtaining a Microsoft certification in Azure Services Overview Upon successful completion of this course, students will be aware of the key topics and concepts taught in the full two-day AZ-900T00 Microsoft Azure Fundamentals Course. This course is a robust introduction to key topics and concepts in the full two-day AZ-900T00: Microsoft Azure Fundamentals course.ÿ The 2-day AZ-900T00 course includes hands-on labs and is the core foundation class that many other Azure courses build off. Core Azure Concepts Introduction to Azure fundamentals Azure fundamental concepts Core Azure architectural components Overview of Core Azure Services Azure database and analytics services Azure compute services Azure Storage services Azure networking services Overview of Core Solutions and Management Tools on Azure Artificial Intelligence Monitoring service for visibility, insight, and outage mitigation Introduction to tools used to manage and configure your Azure environment Azure IoT service for your application Overview of General Security and Network Security Features Protect against security threats on Azure Secure network connectivity on Azure Overview of Identity, Governance, Privacy, and Compliance Features Examine privacy, compliance, and data protection standards on Azure Overview of Azure Cost Management and Service Level Agreements Manage your Azure costs Azure services, SLAs, and service lifecycle

Duration 3 Days 18 CPD hours This course is intended for This course is for IT professionals who manage on-premises Windows Server environments and want to use Azure to manage server workloads and run their virtual workloads on Windows Server 2019. They also want to use existing Microsoft System Center products to implement and manage software-defined datacenters with Windows Server 2019. Overview Describe the Azure Stack portfolio, including Azure Stack HCI, Azure Stack Hub, and Azure Stack Edge Describe the Azure Stack HCI core technologies and management tools. Describe the process of a typical Azure Stack HCI implementation. Identify Azure Stack HCI hybrid capabilities. Implement, manage, and maintain workloads on Azure Stack HCI. Plan for and implement Azure Stack HCI Storage, including Storage QoS and Storage Replica. Plan for Azure Stack HCI Networking. Implement Software Defined Networks in Azure Stack HCI. This three-day course WS-013T00-A is intended primarily for IT Professionals who already have significant experience with managing an on-premises Windows Server environment. Its purpose is to cover advanced topics related to Windows Server software-defined datacenter, Azure Stack HCI, and other Azure Stack products. The course also describes the use of existing Microsoft System Center products to implement and manage software-defined datacenters with Windows Server 2019. This course is advanced and is designed for people that want to run their virtual workloads on Windows Server 2019 at medium-to-large scale using software-defined datacenter and hyper-converged principles. Introducing Azure Stack HCI Overview of Azure Stack HCI Overview of Azure Stack HCI technologies Overview of Azure Stack HCI management tools Overview of the Azure Stack HCI hybrid capabilities Operating and maintaining Azure Stack HCI Implementing and managing workloads on Azure Stack HCI Maintaining Azure Stack HCI Planning for and implementing Azure Stack HCI storage Overview of Azure Stack HCI Storage core technologies Planning for Storage Spaces Direct in Azure Stack HCI Implementing a Storage Spaces Direct-based hyper-converged infrastructure Managing Storage Spaces Direct in Azure Stack HCI Planning for and implementing Storage QoS Planning for and implementing Storage Replica Planning for and implementing Azure Stack HCI networking Overview of Azure Stack HCI core networking technologies Overview of network virtualization and Software-Defined Networking Planning for and implementing Switch Embedded Teaming Planning for and implementing Datacenter Firewall Planning for and implementing Software Load Balancing Planning for and implementing RAS Gateways

Duration 1 Days 6 CPD hours This course is intended for Individuals who have knowledge, skills, and experience developing front-end and/or back-end JavaScript applications for the web stack. Developers who have experience designing, developing, testing, and deploying applications using an object-oriented programming language and would like to transfer those skills to building applications with JavaScript. Overview When you complete this course, you will be able to: Understand the different exam objectives and their weighting on the exam. Know which JavaScript concepts to focus on to best prepare for your exam. Study the provided repository of JavaScript sample code. Are you ready to take the next step in your career by becoming a Salesforce Certified JavaScript Developer I? By covering the details around the exam structure and objectives, this course will help hone your problem-solving skills and reinforce your knowledge of key features and concepts of the JavaScript programming language. This course includes a voucher to sit for the Salesforce JavaScript Developer I certification exam. JavaScript Basics Data Types and Variables Type Conversion (explicit and implicit) Collections Working with Strings, Numbers, and Dates Working with JSON Objects, Functions, and Classes Creating Objects Defining Functions Object Prototypes Declaring Classes Using JavaScript Modules Browser and Events Document Object Model DOM Events Browser Dev Tools Debugging and Error Handling Throwing and Catching Errors Working with the Console Asynchronous Programming Callback Functions Promises Async/Await Server Side JavaScript Node.js CLI Node.js Libraries Debugging in Node.js npm Testing Assertions Types of Testing Additional course details: Nexus Humans Salesforce Certification Preparation for Salesforce JavaScript Developer I (CRT600) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Salesforce Certification Preparation for Salesforce JavaScript Developer I (CRT600) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 5 Days 30 CPD hours This course is intended for This course is for IT Professionals with expertise in designing and implementing solutions running on Microsoft Azure. They should have broad knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platform, budgeting, and governance. Azure Solution Architects use the Azure Portal and as they become more adept they use the Command Line Interface. Candidates must have expert-level skills in Azure administration and have experience with Azure development processes and DevOps processes. Overview Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include virtualization, automation, networking, storage, identity, security, data platform, and application infrastructure. This course outlines how decisions in each theses area affects an overall solution. Implement Azure Active Directory Overview of Azure Active Directory Users and Groups Domains and Custom Domains Azure AD Identity Protection Implement Conditional Access Configure Fraud Alerts for MFA Implement Bypass Options Configure Guest Users in Azure AD Configure Trusted IPs Manage Multiple Directories Implement and Manage Hybrid Identities Install and Configure Azure AD Connect Configure Password Sync and Password Writeback Configure Azure AD Connect Health Implement Virtual Networking Virtual Network Peering Implement VNet Peering Implement VMs for Windows and Linux Select Virtual Machine Size Configure High Availability Implement Azure Dedicated Hosts Deploy and Configure Scale Sets Configure Azure Disk Encryption Implement Load Balancing and Network Security Implement Azure Load Balancer Implement an Application Gateway Understand Web Application Firewall Implement Azure Firewall Implement Azure Front Door Implementing Azure Traffic Manager Implement Storage Accounts Storage Accounts Blob Storage Storage Security Managing Storage Accessing Blobs and Queues using AAD Implement NoSQL Databases Configure Storage Account Tables Select Appropriate CosmosDB APIs Implement Azure SQL Databases Configure Azure SQL Database Settings Implement Azure SQL Database Managed Instances High-Availability and Azure SQL Database In this module, you will learn how to Create an Azure SQL Database (single database) Create an Azure SQL Database Managed Instance Recommend high-availability architectural models used in Azure SQL Database Automate Deployment and Configuration of Resources Azure Resource Manager Templates Save a Template for a VM Evaluate Location of New Resources Configure a Virtual Hard Disk Template Deploy from a template Create and Execute an Automation Runbook Implement and Manage Azure Governance Create Management Groups, Subscriptions, and Resource Groups Overview of Role-Based Access Control (RBAC) Role-Based Access Control (RBAC) Roles Azure AD Access Reviews Implement and Configure an Azure Policy Azure Blueprints Manage Security for Applications Azure Key Vault Azure Managed Identity Manage Workloads in Azure Migrate Workloads using Azure Migrate VMware - Agentless Migration VMware - Agent-Based Migration Implement Azure Backup Azure to Azure Site Recovery Implement Azure Update Management Implement Container-Based Applications Azure Container Instances Configure Azure Kubernetes Service Implement an Application Infrastructure Create and Configure Azure App Service Create an App Service Web App for Containers Create and Configure an App Service Plan Configure Networking for an App Service Create and Manage Deployment Slots Implement Logic Apps Implement Azure Functions Implement Cloud Infrastructure Monitoring Azure Infrastructure Security Monitoring Azure Monitor Azure Workbooks Azure Alerts Log Analytics Network Watcher Azure Service Health Monitor Azure Costs Azure Application Insights Unified Monitoring in Azure

Duration 4 Days 24 CPD hours This course is intended for Students for AZ-600: Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Hub are interested in becoming Azure Stack Hub operators who provide cloud services to end users or customers from within their own datacenter using Azure Stack Hub. Azure Stack Hub operators responsibilities include planning, deploying, packaging, updating, and maintaining the Azure Stack Hub infrastructure. They also offer hybrid cloud resources and requested services and manage infrastructure as a service (IaaS) and platform as a service (PaaS). Overview Prepare for Azure Stack Hub deployment Manage infrastructure certificates for Azure Stack Hub Manage Azure Stack Hub registration Configure an Azure Stack Hub home directory Provision a service principal for Azure Stack Hub Recommend a business continuity disaster recovery (BCDR) strategy Manage Azure Stack Hub by using privileged endpoints Manage Azure Stack Hub Marketplace Offer App Services and Event Hub resource providers Manage usage and billing This course teaches Azure administrators and Azure Stack Hub operators how to plan, deploy, package, update, and maintain the Azure Stack Hub infrastructure. Lessons include deploying Azure Stack Hub, managing the Azure Stack Hub Marketplace, offering App Services and Event Hub resource providers, managing Azure Stack Hub registration, and maintaining system health. Overview of Azure Stack Hub Azure Stack Hub Datacenter integration Azure Stack Hub PowerShell Module review questions Provide Services Manage Azure Stack Hub Marketplace Offer an App Services resource provider Offer an Event Hubs resource provider Offer services Manage usage and billing Module review questions Implement Data Center Integration Prepare for Azure Stack Hub deployment Manage Azure Stack Hub registration Module review questions Manage Identity and Access for Azure Stack Hub Manage multi-tenancy Manage access Module review questions Manage the Azure Stack Hub Infrastructure Manage system health Azure Monitor on Azure Stack Hub Plan and configure business continuity and disaster recovery Manage capacity Update infrastructure Manage Azure Stack Hub by using privileged endpoints Module review questions Additional course details: Nexus Humans AZ-600T00 Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Hub training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the AZ-600T00 Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Hub course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is as follows: System Engineers Network Engineers Technical Architects Technical Support Personnel Channel Partners Resellers Overview Upon completing the course, the learner will be able to meet these overall objectives: Describe Cisco SD-Access and how it relates to Cisco DNA Orchestrate a Cisco SD-Access solution using the Cisco DNA Center™ orchestration platform Use the Network Data Platform to demonstrate the assurance and analytics capabilities of SD-Access The Deploying Cisco SD-Access (ENSDA) v1.0 course is an instructor-led, lab based, hands-on course that teaches students how to successfully deploy the Cisco© Software-Defined Access (SD-Access) solution within their enterprise networks. The course discusses how Cisco SD-Access fits into the Cisco Digital Network Architecture (Cisco DNA?). It covers SD-Access fundamentals, provisioning, policies, wireless integration, border operations, and migration strategies. Module 1: Cisco SD-Access Overview Lesson 1: Exploring Cisco SD-Access Lesson 2: Describing the Cisco SD-Access Architecture Lesson 3: Exploring Cisco DNA Center Lesson 4: Configuring Underlay Automation Module 2: Cisco SD-Access Implementation Lesson 1: ISE Integration in DNA Center Lesson 2: Policy Provisioning Basics Lesson 3: Navigating and Managing the Policy Application Workflows Module 3: Cisco SD-Access Border Operations Lesson 1: Cisco SD-Access Deployment Models Lesson 2: Connecting the Fabric to External Domains Module 4: Wireless Integration Orchestration Lesson 1: Integrating Wireless with the Cisco SD-Access Solution Lesson 2: Workflow of Cisco SD-Access Wireless Lesson 3: Cisco SD-Access Wireless Network Design Lesson 4: Cisco SD-Access Wireless Basic Operation Module 5: Cisco SD-Access Assurance and Migration Lesson 1: Cisco Network Data Platform Lesson 2: Cisco SD-Access Migration Strategies

Duration 2 Days 12 CPD hours This course is intended for Administrators Overview Please refer to course overview This offering covers the fundamental concepts of installing and configuring IBM Cognos Analytics, and administering servers and content, in a distributed environment. In the course, participants will identify requirements for the installation and configuration of a distributed IBM Cognos Analytics software environment, implement security in the environment, and manage the server components. Students will also monitor and schedule tasks, create data sources, and manage and deploy content in the portal and IBM Cognos Administration. Introduction to IBM Cognos Analytics administration IBM Cognos Analytics components Administration workflow IBM Cognos Administration IBM Cognos Configuration Identify IBM Cognos Analytics architecture Features of the IBM Cognos Analytics architecture Examine the multi-tiered architecture, and identify logging types and files Examine IBM Cognos Analytics servlets Performance and installation planning Balance the request load Configure IBM Cognos Analytics Secure the IBM Cognos Analytics environment Identify the IBM Cognos Analytics security model Define authentication in IBM Cognos Analytics Define authorization in IBM Cognos Analytics Identify security policies Secure the IBM Cognos Analytics environment Administer the IBM Cognos Analytics server environment Administer IBM Cognos Analytics servers Monitor system performance Manage dispatchers and services Tune system performance, and troubleshoot the server Audit logging Dynamic cube data source administration workflow Manage run activities View current, past, and upcoming activities Manage schedules Manage content in IBM Cognos Administration Data sources and packages Manage visualizations in the library Deployment Other content management tasks Examine departmental administration capabilities Create and manage team members Manage activities Create and manage content and data Manage system settings Manage Themes, Extensions, and Views Share services with multiple tenants

Duration 5 Days 30 CPD hours This course is intended for This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. Overview In this course, you will learn to: Use data science principles to address business issues. Apply the extract, transform, and load (ETL) process to prepare datasets. Use multiple techniques to analyze data and extract valuable insights. Design a machine learning approach to address business issues. Train, tune, and evaluate classification models. Train, tune, and evaluate regression and forecasting models. Train, tune, and evaluate clustering models. Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance. For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform?by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Extracting, Transforming, and Loading Data Topic A: Extract Data Topic B: Transform Data Topic C: Load Data Analyzing Data Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Use Visualizations to Analyze Data Topic D: Preprocess Data Designing a Machine Learning Approach Topic A: Identify Machine Learning Concepts Topic B: Test a Hypothesis Developing Classification Models Topic A: Train and Tune Classification Models Topic B: Evaluate Classification Models Developing Regression Models Topic A: Train and Tune Regression Models Topic B: Evaluate Regression Models Developing Clustering Models Topic A: Train and Tune Clustering Models Topic B: Evaluate Clustering Models Finalizing a Data Science Project Topic A: Communicate Results to Stakeholders Topic B: Demonstrate Models in a Web App Topic C: Implement and Test Production Pipelines